There exist conventional techniques for detecting a number of characteristic points (feature points) within an image and extracting a feature amount within a local region around each feature point (local feature amount) in order to vigorously identify a subject in the image (e.g., a picture, a building, a printed matter, etc.) in accordance with the changes in imaging size and angle, as well as occlusions. Patent Document 1, for example, discloses an apparatus that uses a SIFT (Scale Invariant Feature Transform) feature amount.
The apparatus using a SIFT feature amount first detects a number of feature points from one image (referred to as first image) and generates a local feature amount from the coordinate position, scale (size), and angle of each of these feature points. Based on a local feature amount group consisting of these many generated local feature amounts, a local feature amount group associated with the first image is collated with a local feature amount group associated with a second image, whereby the identical or similar subjects in the images can be identified.
By “similar,” it means that the subjects vary partially, that only certain parts of the subjects are displayed, or that the subjects look differently due to different angles for imaging the subjects in the images.
Patent Document 1: U.S. Pat. No. 6,711,293
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